Senior Process Engineer
ONEOK
Principal Detection Engineer
Hewlett Packard Enterprise
full-time
Posted on:
Location Type: Hybrid
Location: Spring • California, Texas • 🇺🇸 United States
Visit company websiteSalary
💰 $117,500 - $270,000 per year
Job Level
Lead
Tech Stack
AWSAzureCloudCyber SecurityGoGoogle Cloud PlatformJavaPythonPyTorchScikit-LearnSQLTensorflow
About the role
- Design, develop, and implement advanced threat detection systems leveraging ML/AI techniques to identify malicious activity, anomalies, and emerging risks
- Build and optimize machine learning models for real-time detection, including supervised, unsupervised, and reinforcement learning approaches
- Data engineering and pre-processing for cybersecurity applications
- Analyze large-scale datasets to extract meaningful insights, detect patterns, and enhance the accuracy of detection systems
- Develop and refine detection algorithms for intrusion detection, anomaly detection, endpoint security, behavioral analysis, and other cybersecurity applications
- Automate detection workflows and processes to improve efficiency and scalability of security monitoring systems
- Work closely with threat intelligence, red team, security operations, and data scientists, to integrate detection models into security platforms and tools
- Test, validate, and monitor the performance of detection models, ensuring reliability and minimizing false positives/negatives
- Stay up to date with emerging threats, ML/AI technologies, and advancements in cybersecurity to continuously improve detection systems
- Maintain clear documentation of models, processes, and methodologies for knowledge sharing across teams.
Requirements
- Bachelor’s or master’s degree in computer science, cybersecurity, data science, or related engineering field
- Certifications such as CISSP, CISM, CEH or OSCP preferred
- Proven experience (8+ years) in cybersecurity, with a focus on threat detection and response
- Deep understanding of cybersecurity frameworks and concepts, including attack vectors, threat landscapes, and defense mechanisms
- Familiarity with SIEM/SOAR/ and EDR/XDR platforms
- Strong expertise in Machine Learning (ML) and Artificial Intelligence (AI), including model design, training, and deployment
- Knowledge of adversarial machine learning and techniques for defending against model exploitation
- Experience with anomaly detection, behavioral Modeling, and predictive analytics in cybersecurity contexts
- Experience with deep learning architectures or natural language processing (NLP) applied to cybersecurity
- Experience integrating machine learning models into security operations workflows in enterprise environments
- Proficiency in languages such as Python, Go, SPL, YaraL, R , Java, SQL and frameworks like TensorFlow, PyTorch, or Scikit-learn
- Hands-on experience with big data technologies and cloud environments (AWS, Azure, GCP)
- Familiarity with regulatory requirements and compliance frameworks (e.g., GDPR, NIST, ISO 27001).
Benefits
- Health & Wellbeing
- Personal & Professional Development
- Unconditional Inclusion
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
machine learningartificial intelligenceanomaly detectionbehavioral modelingpredictive analyticsdeep learningnatural language processingdata engineeringmodel designmodel training
Soft skills
collaborationcommunicationproblem-solvinganalytical thinkingattention to detail
Certifications
CISSPCISMCEHOSCP
